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Hi!
I'm Ilkin

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I am
a Data Scientist

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About Us

Who Am I?

I'm Ilkin Azimzade — a multidisciplinary technologist with a passion for data, innovation, and real-world problem-solving. With a strong foundation in geospatial analysis, programming, and logistics, I'm currently pursuing a Ph.D. in Management Information Systems.

My journey has taken me through hands-on technical roles, team leadership, and international academic programs, all fueled by a drive to connect systems, people, and ideas through smart, data-driven solutions. Whether it's robotics, 3D printing, or geodata science, I thrive at the intersection of technology and impact.

Robotics & Automation

Building intelligent systems and humanoid robots combining hardware and software design.

Geospatial & GIS

Expert in remote sensing, GNSS, and geospatial analysis using QGIS, ArcGIS, EGMS & SNAP.

Data Science

Proficient in Python, R, and machine learning, with experience in both system-level and field applications.

Prototyping & 3D Printing

Designing and printing functional parts for robotics and experimental systems using digital fabrication tools.

Cups of coffee

Projects

Courses I Have Completed

Events Volunteered

My Specialty

My Skills

I combine strong coding, spatial analysis, and hardware skills to solve real-world problems—from geospatial data pipelines to smart robotics systems.

Python

50%

R

20%

SQL

10%

C++

25%

HTML/CSS/JS

30%

Remote Sensing (QGIS, SNAP, EGMS)

70%

Education

Ph.D. in Management Information Systems

This portfolio showcases my academic and professional journey focused on geospatial technologies, machine learning, and smart decision support systems. My goal is to present real-world applications of data science and geospatial analysis in areas such as urban hazard monitoring, environmental sustainability, and intelligent system design. The portfolio includes selected research projects, code samples (Python, R), visualizations, and systematic reviews, demonstrating both technical skills and interdisciplinary problem-solving.

Focus: Integration of geospatial data, machine learning, and cloud-based DSS for real-time urban disaster response.
Geospatial Intelligence: Utilized satellite imagery (Sentinel, Landsat), LiDAR, and UAVs for multi-hazard detection.
Machine Learning Models: Applied supervised (Random Forests, Decision Trees), unsupervised (Clustering), and deep learning (CNN, RNN) techniques for predictive geohazard modeling.
System Integration: Identified the research gap in real-time, end-to-end systems for urban resilience planning.
Tools & Languages: Leveraged Python and R for data processing, ML model development, and geospatial analysis.
Future Vision: Advocated for explainable AI, user-centered DSS design, and cross-city deployment for smart, resilient cities.

M.Sc. in Geomatics for Mineral Resource Management (Double Degree)

An interdisciplinary program combining remote sensing, GIS, and geospatial data analysis. Master's thesis focused on land deformation monitoring using InSAR and EGMS datasets. This program provided extensive hands-on experience with tools like SNAP, QGIS, and satellite imagery analysis for sustainable resource management.

B.Sc. in Oil and Gas Equipment Engineering

A strong engineering foundation focused on petroleum systems, pipeline design, and technical operations in the energy industry. Covered both theoretical knowledge and practical skills in oil and gas technologies, preparing for real-world engineering roles.

Experience